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The Art and Science of Data Visualization: A Data Bootcamp

This one-and-a-half-day bootcamp explores practical, strategic, and theoretical approaches to data visualization in higher education. The experience begins on Monday morning with an opening session, is followed by 5 breakout sessions (90 minutes each),
and ends on Tuesday with a closing session. Participants select specific breakout sessions to customize the bootcamp based on their interests. The data bootcamp is a complete experience; the content is not offered à la carte.

Schedule and Breakout Session Options

Monday

8:00-8:45 AM: Opening Session

9:00-10:30 AM: Breakout Session A (choose one topic)

At times, decision-makers do not fully appreciate the value of data visualizations. We do our field a disservice when reports and white papers do not convey compelling stories and fail to communicate the power of using data to inform decisions. Used effectively, data visualizations provide clarity across space and time, allow us to peek into the minds of students and communities, and provide context with similar institutions across the country. Data visualizations help transform our understanding of problems and lead us to solutions.

We are integral in building meaningful data narratives to drive reflection and action. During this session, we share how to craft a narrative, or story, using data and select data visualizations – exploring why those results are relevant, to which audiences, and how they fit into a larger narrative. This session will assist you in your role as a storyteller (using principles of storytelling and various narrative resources) and will help you identify when data visualizations can add value to a narrative. This session will also help you build a culture of evidence-based storytelling at your institution.

For over a decade, private industry has hired data scientists faster than they could be produced. In 2012, Thomas Davenport and D.J. Patil wrote in the Harvard Business Review that the data scientist was “the sexiest job of the 21st century” causing it to become a buzzword. In 2015, Dr. Patil was appointed by President Obama to serve as the Chief Data Scientist of the U.S. Office of Science and Technology Policy which led to the establishment of nearly forty Chief Data Officer roles across the federal government. In this session, we explore the history of data science, the role of the data scientist in higher education, and the career path for a new breed of analyst called the “data science communicator”.

Regardless of the tool used, there are a variety of cognitive and perceptual characteristics that can be used to improve a data visualization. Certain visual items are processed faster and are more intuitively clear, while others can slow down your audience’s ability to understand your point or can conceal your point entirely. This session teaches you how visualizations are processed by the human brain and how you can make your visualizations clearer and easier to understand.

A successful long-term data visualization strategy demands that we understand and work with end-users. Even the best data visualization is rendered meaningless if it is not used. To this end, it is important that data designers take into consideration not only the best visualization practices, but also how to build relationships with institutional stakeholders to ensure that visualizations are used (and used appropriately).

11:00-12:30 PM: Breakout Session B (choose one topic)

When the president or provost (or another stakeholder) asks for a dashboard, we often invest time, effort, and/or money in a technical solution or start building a format using existing data. Sadly, some of those efforts result in reports or dashboards that go unused. Often, the disconnect lies between the fact that we produced something great—but not great for users. This session focuses on tools and methods that help you gain understandings of your users’ needs and begin to translate those needs into application.

A successful long-term data visualization strategy demands that we understand and work with end-users. Even the best data visualization is rendered meaningless if it is not used. To this end, it is important that data designers take into consideration not only the best visualization practices, but also how to build relationships with institutional stakeholders to ensure that visualizations are used (and used appropriately).

Information begins as a pile of numbers and letters with little organization and no implicit prioritization. But, within that jumble of numbers and letters are gems of information. How do you turn those gems into compelling stories that can be consumed by a broad audience? This session teaches you how to identify your information gems and turn those gems into a story that will engage your audience and drive positive results.

Tableau is a popular data visualization tool that allows data professionals to share insights about their institutions with key university leaders and stakeholders. There is increasing interest in using visualizations to share institutional information with prospective students and other stakeholders. In this session, we will discuss best practices for developing public-facing visuals in Tableau, such as common chart types, suppressing low Ns to protect anonymity, ensuring ease-of-use for large audiences, and product promotion. The session will use survey data as the predominant example, but the details apply to other types of institutional data as well.

Understanding Tableau’s unique terminology and knowing how to connect to data in the optimal format are fundamental to using it for effective data visualizations. In this session, you will learn Tableau’s terminology and best practices for connecting to and structuring your data to support data visualizations and reporting.

In this session, we demonstrate how to automate data preparation and visualization using Power BI. You will build a conceptual understanding of how tools, such as Power BI, can be utilized to meet a variety of data needs, including combining survey and SIS data, cleaning and transforming data, and creating useful interactive reports. In addition, you will be provided with Power BI sample files, templates, and detailed walkthroughs to reference for your journey to visualize assessment data.

1:45-3:15 PM: Breakout Session C (choose one topic)

This session takes a case study approach to examine how one institution developed and implemented a public enrollment dashboard using Power BI and Excel census files. We discuss the key steps in the process, including selecting Power BI, designing the dashboard to meet institutional needs, and the ongoing management of the dashboard and data sources. We also discuss lessons learned and future plans.

It’s frustrating when we invest a lot of time and effort in a dashboard only to have to go back to the drawing board and start over. This session explores ideas related to ideation, iteration, prototyping, and gathering feedback in the design of a dashboard. Learning to ideate and iterate effectively provides structured techniques that facilitate the brainstorming and decision processes. Quickly prototyping ideas and gathering feedback is a way to ensure that ideas that emerge from a design process are improved prior to developing them. By applying these approaches to your work, you can speed up the process of design and development, which will potentially allow you to increase the throughput of your offices, improve stakeholder satisfaction with your products, and promote wider use of those products.

One way to share survey results with stakeholders is to visualize those data using Tableau; getting your data in the right format is key. In this session, you will learn how to transform and shape your survey data for visualization in Tableau. Topics covered include cleaning your data, ensuring anonymity for small N studies, and designing for your audience.

Automating and visualizing data effectively requires a variety of knowledge and skills. However, understanding how to create and design visualizations is only part of the picture. This session is a guided discussion about why we visualize data, how we might better serve end users who utilize data for decisions, and how we can more fully understand the impact of shifting from static, descriptive reports to interactive data visualizations.

Regardless of the tool used, there are a variety of cognitive and perceptual characteristics that can be used to improve a data visualization. Certain visual items are processed faster and are more intuitively clear, while others can slow down your audience’s ability to understand your point or can conceal your point entirely. This session teaches you how visualizations are processed by the human brain and how you can make your visualizations clearer and easier to understand.

For over a decade, private industry has hired data scientists faster than they could be produced. In 2012, Thomas Davenport and D.J. Patil wrote in the Harvard Business Review that the data scientist was “the sexiest job of the 21st century” causing it to become a buzzword. In 2015, Dr. Patil was appointed by President Obama to serve as the Chief Data Scientist of the U.S. Office of Science and Technology Policy which led to the establishment of nearly forty Chief Data Officer roles across the federal government. In this session, we explore the history of data science, the role of the data scientist in higher education, and the career path for a new breed of analyst called the “data science communicator”.

3:45-5:15 PM: Breakout Session D (choose one topic)

Supporting senior leaders’ decision-making is a key function our work. In this session, you will learn how to visualize National Student Clearinghouse (NSC) data in Tableau to address questions about non-enrolled applicants and students who have left an institution. We will also discuss how working with and understanding senior leaders’ needs informs the types of visualizations used, and how the process for developing materials that inform and support decision-making precede a hands-on project.

We are integral in building meaningful data narratives to drive reflection and action. During this session, we share how to craft a narrative, or story, using data and select data visualizations – exploring why those results are relevant, to which audiences, and how they fit into a larger narrative. This session will assist you in your role as a storyteller (using principles of storytelling and various narrative resources) and will help you identify when data visualizations can add value to a narrative. This session will also help you build a culture of evidence-based storytelling at your institution.

Building on the presentation of Stephanie Evergreen at the 2018 AIR Forum, this session helps you identify the elements that make a good (and bad) data visualization. Employing a highly visual and interactive format, you will review a series of data requests and ask, “Should this report include data visualization?” If the answer is YES, we will discuss why and how to pinpoint the data of interest, why and how to choose the right visual, why and how to comply with institution-preferred design standards, and why and how to tell a story.

It’s frustrating when we invest a lot of time and effort in a dashboard only to have to go back to the drawing board and start over. This session explores ideas related to ideation, iteration, prototyping, and gathering feedback in the design of a dashboard. Learning to ideate and iterate effectively provides structured techniques that facilitate the brainstorming and decision processes. Quickly prototyping ideas and gathering feedback is a way to ensure that ideas that emerge from a design process are improved prior to developing them. By applying these approaches to your work, you can speed up the process of design and development, which will potentially allow you to increase the throughput of your offices, improve stakeholder satisfaction with your products, and promote wider use of those products.

Many of us share institutional data internally with interested stakeholders. But are you prepared to make those data public? In other words, are you able to navigate the data and design challenges of producing an interactive visualization that will be used by audiences you don’t know? What about issues around displaying sensitive information? This session covers best practices for developing highly public data visualizations, including identifying target audiences, ensuring ease of use, user testing, inter-office collaboration, product promotion, and how to deal with issues of respondent anonymity.

A wealth of data are collected throughout a student’s educational career to better understand their experience; those data are aggregated and used as evidence in improvement efforts. But, are those data easily accessible and consumable by all stakeholders? As higher education data and analytics professionals, it is our responsibility to ensure that the information we produce can be used to improve the student experience. In this session, we explore how we can serve as advocates of student success data, how we can design visualizations and dashboards that clearly tells the student success story, and the types of data that should be used in those visualizations and dashboards.

Tuesday

8:00 - 9:00 AM: Coffee and Networking

9:00 - 10:30 AM: Breakout Session E (choose one topic)

How should we engage faculty when deciding what data to report and the types of data visualizations to use? How do data reporting and visualization reflect what faculty need to know to improve their teaching and support student success? How should we encourage data-informed faculty decision-making? In this session, we address these questions and explore strategies and tools for producing faculty-informed data reporting and visualization. You are encouraged to share your experiences and best practices of collaboration with faculty to ensure that data reporting and visualizations are relevant and meaningful.

Information begins as a pile of numbers and letters with little organization and no implicit prioritization. But, within that jumble of numbers and letters are gems of information. How do you turn those gems into compelling stories that can be consumed by a broad audience? This session teaches you how to identify your information gems and turn those gems into a story that will engage your audience and drive positive results.

Power BI is a complex tool with many advanced features that allow for automation and analyses. In this session, we demonstrate ways to use Power BI to its fullest extent to benefit both beginners and advanced users. Tips include data cleaning and modeling, troubleshooting, and ensuring that reports work for various audiences. Sample data, Power BI reports, and detailed walkthroughs will be provided so you can practice these strategies.

The proverb “a picture is worth a thousand words” means that well-designed data visualizations can convey large amounts of information more quickly and effectively than the best worded narratives. Unfortunately, we often believe that our reports are not read or our dashboards not explored to make informed decisions. And, oftentimes we blame the reader of the report as not having the data literacy necessary to understand the information presented. But, what if we looked at the problem another way – through the eyes of the senior leader? In this interactive session, we explore the challenges facing senior leaders in data communication and discuss strategies we can use to better communicate our information at the senior level.

The key to a good dashboard is having a clear purpose and understanding the needs of its intended audience. In this session, participants will consider the frequency of data updates, the audience, and the overall purpose of the dashboard. Using three case studies, we will discuss how to build a strategic dashboard, an operational dashboard, and an analytical dashboard.

While data visualizations are powerful for the end-user, there are other valuable reasons to explore the use of visualization software – as a coaching and consulting tool. Data visualizations are processed faster than tabulated data and allows us to see obscure patterns and trends much easier. In addition, having the end user engaged in the exploration and creation of visual representations will increase the data literacy of that user. In this session, we explore the lesser-used reasons to use data visualization software: to allow analysts to explore and better understand institutional data trends, to build our stakeholders’ literacy by engaging them in the visualization development process, and to build the competencies of other institutional units to incorporate visualizations in their work.